Adaptive Hierarchical Similarity Metric Learning With Noisy Labels-Reference-Cited by-同舟云学术

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Adaptive Hierarchical Similarity Metric Learning With Noisy Labels

Published:2023 Issue: Volume:32 Page:1245-1256
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Yan Jiexi¹,Luo Lei²,Deng Cheng³^ORCID,Huang Heng⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Xidian University, Xi’an, China

2. JD Finance American Corporation, Mountain View, CA, USA

3. School of Electronic Engineering, Xidian University, Xi’an, China

4. Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA

Funder

Key Research and Development Program of Shaanxi Province

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10041006.pdf?arnumber=10041006

Reference70 articles.

1. Deep Metric Learning with Angular Loss

2. ReMixMatch: Semi-supervised learning with distribution alignment and augmentation anchoring;berthelot;arXiv 1911 09785,2019

3. Robust Distance Metric Learning via Bayesian Inference

4. Improved baselines with momentum contrastive learning;chen;arXiv 2003 04297,2020

5. Deep Adversarial Metric Learning

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1. Mitigating data imbalance and noise: A divergence-based approach with enhanced sample selection;Neurocomputing;2024-11

2. HSALC: hard sample aware label correction for medical image classification;Multimedia Tools and Applications;2024-09-02

3. Tackling Noisy Labels With Network Parameter Additive Decomposition;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-09

4. Learning Dynamic Batch-Graph Representation for Deep Representation Learning;International Journal of Computer Vision;2024-07-19

5. Mixture correntropy-based robust distance metric learning for classification;Knowledge-Based Systems;2024-07

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